Results 41 to 50 of about 1,698,574 (297)
Adaptive Kernel Graph Nonnegative Matrix Factorization
Information, 2023 Nonnegative matrix factorization (NMF) is an efficient method for feature learning in the field of machine learning and data mining. To investigate the nonlinear characteristics of datasets, kernel-method-based NMF (KNMF) and its graph-regularized ...
Rui-Yu Li, Yu Guo, Bin Zhang
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A fast algorithm for matrix balancing [PDF]
, 2013 As long as a square nonnegative matrix A contains sufficient nonzero elements, then the matrix can be balanced, that is we can find a diagonal scaling of A that is doubly stochastic. A number of algorithms have been proposed to achieve the balancing, the
Knight, Philip, Ruiz, Daniel
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Guided Semi-Supervised Non-Negative Matrix Factorization
Algorithms, 2022 Classification and topic modeling are popular techniques in machine learning that extract information from large-scale datasets. By incorporating a priori information such as labels or important features, methods have been developed to perform ...
Pengyu Li +6 more
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On Identifiability of Nonnegative Matrix Factorization [PDF]
IEEE Signal Processing Letters, 2018 In this letter, we propose a new identification criterion that guarantees the recovery of the low-rank latent factors in the nonnegative matrix factorization (NMF) model, under mild conditions. Specifically, using the proposed criterion, it suffices to identify the latent factors if the rows of one factor are \emph{sufficiently scattered} over the ...
Xiao Fu 0001 +2 more
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Approximating a similarity matrix by a latent class model: A reappraisal of additive fuzzy clustering [PDF]
, 2009 Let Q be a given n×n square symmetric matrix of nonnegative elements between 0 and 1, similarities. Fuzzy clustering results in fuzzy assignment of individuals to K clusters.
Braak, C.J.F., ter +3 more
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Scalable non-negative matrix tri-factorization
BioData Mining, 2017 Background Matrix factorization is a well established pattern discovery tool that has seen numerous applications in biomedical data analytics, such as gene expression co-clustering, patient stratification, and gene-disease association mining.
Andrej Čopar +2 more
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NIMFA: A Python Library for Nonnegative Matrix Factorization [PDF]
, 2012 NIMFA is an open-source Python library that provides a unified interface to nonnegative matrix factorization algorithms. It includes implementations of state-of-the-art factorization methods, initialization approaches, and quality scoring.
Zupan, Blaz, Zitnik, Marinka
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Computing a Nonnegative Matrix Factorization---Provably [PDF]
SIAM Journal on Computing, 2012 In the nonnegative matrix factorization (NMF) problem we are given an $n \times m$ nonnegative matrix $M$ and an integer $r > 0$. Our goal is to express $M$ as $A W$, where $A$ and $W$ are nonnegative matrices of size $n \times r$ and $r \times m$, respectively. In some applications, it makes sense to ask instead for the product $AW$ to approximate $
Sanjeev Arora +3 more
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Minimal positive realizations of transfer functions with nonnegative multiple poles [PDF]
, 2005 This note concerns a particular case of the minimality problem in positive system theory. A standard result in linear system theory states that any nth-order rational transfer function of a discrete time-invariant linear single-input-single-output (SISO)
Matolcsi, Máté, Nagy, B.
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Collaborative filtering based on nonnegative/binary matrix factorization
Frontiers in Big DataCollaborative filtering generates recommendations by exploiting user-item similarities based on rating data, which often contains numerous unrated items.
Yukino Terui +5 more
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